Evidence map›Paper›PMID 41900776›Full record

ReviewPharmaceutics2026

Design and Application of Intelligent Local Anesthetic Nanoformulations.

Peng Ke, Yuying Li, Min Han, Xiaodan Wu

Abstract readReview
In one paragraph

Review in Pharmaceutics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Peng KeDepartment of Anesthesiology, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Shengli Clinical Medical College of Fujian Medical University, Fuzhou 350001, China.ORCID 0009-0002-0329-9901
Yuying LiDepartment of Anesthesiology, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Shengli Clinical Medical College of Fujian Medical University, Fuzhou 350001, China.
Min HanInstitute of Pharmaceutics, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
Xiaodan WuDepartment of Anesthesiology, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Shengli Clinical Medical College of Fujian Medical University, Fuzhou 350001, China.

Funding

Fujian provincial health technology project 2023QNA012National Natural Science Foundation of China No. 82271238
6 · The paper itself

Abstract

Local analgesia is a prevalent and cost-effective pain management strategy with minimal systemic side effects. At the same time, nanotechnology has been employed to achieve the sustained release of drugs to prolong the duration of local anesthetics (LAs). However, these traditional nanoformulations lack responsiveness and thus cannot achieve precise pain relief through on-demand administration. The emergence of "intelligent" nanosystems with stimulus-response capabilities has opened up new prospects in pain control. This review summarizes recent advancements in the design and application of triggerable LAs nanoformulations that can be activated by external stimuli such as light, ultrasound, or heat. These systems facilitate precise, patient-specific pain management, transforming the clinical approach from long-term suppression to controllable and on-demand relief. Finally, we discussed the current challenges and future prospects. A deeper understanding of this field will facilitate the development of superior analgesic solutions and ultimately improve the treatment outcomes for patients.

Indexed as

intelligent drug deliverylocal anestheticsnanotechnologyon-demand analgesiatriggered release

Identifiers

PMID41900776
PMCPMC13029617

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.